Inha University

In the original publication [...].

Purpose This study aims to explore how cultural interest in the Korean Wave (Hallyu) influences the distribution and performance of Korean restaurants across US regions. It examines the intersection of cultural trends, consumer behavior and regional business outcomes, offering insights into the geographical dynamics of ethnic restaurant growth. Design/methodology/approach This study analyzes 1,228,596 Yelp reviews from 4,585 Korean restaurants across the 150 most populous US cities. A Hallyu Influence Index was developed using Python’s Pytrends library, based on 46 Hallyu-related keywords sourced from the Korea Culture and Information Service. Google Trends data (2004–2023) were used to capture regional cultural interest over time. A mixed-effects model was used to account for both fixed regional trends and random state-level variations. Interaction terms tested whether the cultural impact differed by region. The dependent variable, the number of Korean restaurants, was transformed using the Box-Cox method for model optimization. Findings The Hallyu Influence Index significantly predicted the number of Korean restaurants across states. While the West had the highest baseline presence, regions such as the Midwest and South showed stronger marginal effects of Hallyu. This suggests regional variation in how cultural trends influence restaurant growth, supporting the importance of cultural interest as a driver of business success. Originality/value This study introduces a novel Hallyu Influence Index to measure regional cultural interest and links it to real-world business data. It bridges big data analytics, acculturation theory and geospatial approaches, offering actionable insights for tourism marketers and hospitality professionals seeking to leverage cultural trends in market strategy.

Quantitative risk thresholds for interstitial lung abnormalities (ILAs) and their association with long-term outcomes remain unclear in health screening populations. In this retrospective study, individuals aged ≥ 50 years who underwent chest CT between 2007 and 2013 were analyzed. Baseline CT scans were independently reviewed by two chest radiologists and categorized as none, equivocal ILA, or ILA, with consensus adjudication. ILA extent was quantified using a deep learning–based approach, including total ILA% and fibrotic ILA% across the whole lung. Multivariable Cox proportional hazards models were used to assess associations between ILA extent and clinical outcomes, including interstitial lung disease diagnosis, lung cancer diagnosis, and all-cause mortality. Optimal thresholds were determined using the minimum P-value method. Among 3,363 participants, 73 (2.2%) had ILA and 124 (3.7%) had equivocal ILA. The optimal cutoffs for all-cause mortality were 2.89% for total ILA and 0.26% for fibrotic ILA. Participants with total ILA ≥ 2.89% (HR, 5.15; P < 0.001) or fibrotic ILA ≥ 0.26% (HR, 2.71; P < 0.001) had significantly higher mortality risks compared with those below these thresholds. Deep learning–based quantitative ILA assessment was independently associated with long-term mortality, with prognostic thresholds of 3% for total ILA and 0.3% for fibrotic ILA in a health screening population.

Stimuli-responsive hydrogels, also referred to as "smart" hydrogels, have emerged as versatile platforms for a wide range of biological and biomedical applications owing to their tunable physical, chemical, and biocompatible properties. Their adaptability arises from both their ability to undergo reversible swelling-deswelling and volume phase transitions in response to specific physicochemical or biological stimuli and the diversity of synthesis strategies that enable precise tailoring of material properties to meet distinct biomedical demands. Recent advances have led to the development of novel hydrogel designs with improved swelling-deswelling behavior, enhanced stimulus sensitivity, and superior biocompatibility, thereby expanding their applicability in complex biological environments. Despite this progress, challenges such as precise control over hydrogel size and relatively slow response kinetics remain critical barriers to broader biomedical and clinical translation. Addressing these limitations requires strategies, including reducing hydrogel particle dimensions to accelerate response rates and engineering heterogeneous or highly porous gel architectures to increase functional surface area. This review provides a comprehensive classification of stimuli-responsive hydrogels based on their physical properties and response mechanisms, and summarizes recent innovations in their design, synthesis, and biomedical applications. Furthermore, it discusses emerging approaches to enhance the clinical applicability of smart hydrogels in controlled drug release, targeted gene delivery, biosensor development, and tissue engineering. Overall, continued optimization of swelling-deswelling characteristics and material design will be essential to fully realize the potential of stimuli-responsive hydrogels in precision medicine and advanced therapeutic applications.